Deep Learning Approach for Automatic Classification of Ocular and Cardiac Artifacts in MEG Data
We propose an artifact classification scheme based on a combined deep and convolutional neural network (DCNN) model, to automatically identify cardiac and ocular artifacts from neuromagnetic data, without the need for additional electrocardiogram (ECG) and electrooculogram (EOG) recordings. From ind...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
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| Series: | Journal of Engineering |
| Online Access: | http://dx.doi.org/10.1155/2018/1350692 |
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